Real-time tracking of offline transactions

ABSTRACT

An online system receives offline conversion data in real-time from a third party system regarding an offline user, the offline conversion data indicating an action performed by the offline user and identifying information for the offline user. The online system identifies a local user matching the offline user based on the identifying information for the offline user. The online system stores the offline conversion for the identified local user. The online system determines an attribution to a sponsored content item for the offline conversion. The online system presents updated information regarding the offline conversion to the third party system in real-time.

BACKGROUND

This disclosure relates generally to online systems, and in particularto real-time tracking of offline transactions.

Certain online systems, such as social networking systems, allow theirusers to connect to and to communicate with other online system users.Users may create profiles on such an online system that are tied totheir identities and include information about the users, such asinterests and demographic information. The users may be individuals orentities such as corporations or charities. Because of the increasingpopularity of these types of online systems and the increasing amount ofuser-specific information maintained by such online systems, an onlinesystem provides an ideal forum for third parties to increase awarenessabout products or services to online system users.

In some cases, after a target user is presented with information by theonline system regarding a third party system's products, services, orother information, the online system may subsequently be able to trackif the target user acts upon such information. For example, the targetuser may perform the action on the website of the third party system.This website includes a tracking mechanism linked with the online systemthat allows the online system to directly track the subsequent action.By tracking the subsequent actions performed by users after beingpresented with information from the third party systems, the onlinesystem is able to provide the third party system with accurateinformation regarding the effectiveness of providing the information tothe target users. However, in some cases, a target user who is presentedby the online system with information about products or services at theonline system may subsequently act upon this information offline, or insuch a way that the subsequent action is not directly trackable. As thesubsequent action is not directly trackable, the online system may notbe able to provide accurate information to the third party systemregarding the effectiveness of the information presented by the onlinesystem.

SUMMARY

Embodiments of the invention include an online system that may trackoffline transactions and other actions from third party systems in realtime. The online system receives information about actions performed byusers at the online system that may not be directly trackable, such as atransaction made at a physical location. This is in contrast to actionsthat may be directly trackable, such as one made at a website of thethird party system. By using such a method, the online system is able tomore accurately determine the effects of providing sponsored contentfrom the third party systems and the benefits provided to the thirdparty systems by the sponsored content. While previously the offlineconversion information may not be accurately determined, and thus alarge portion of the effect of the sponsored content may not be measuredaccurately, by having the offline conversions information be gatheredand reported in real-time, the online system is able to more accuratelypresent the information to the third party system, allowing the thirdparty system to better understand the effects of its sponsored content.

In particular, in an embodiment, the online system receives offlineconversion data from a third party system for an offline user, theoffline conversion data including an indication of an action performedby the offline user that is not directly trackable and identifyinginformation for the offline user, the offline conversion data receivedsubstantially immediately after the action. In one embodiment, theonline system receives the offline conversion data via an applicationprogramming interface provided by the online system to the third partysystem. In one embodiment, the action is not directly trackable by theonline system via a website of the third party system. In oneembodiment, the action comprises at least one of: a transaction at aphysical location, a transaction as part of a delayed payment service, atransaction as part of a service approval process, and a transactioncompleted at an intermediary. For example, the action could be acompletion of a transaction that was started online, where a product orgood was selected online, and payment for the good was made at aphysical location.

The online system identifies a local user matching the offline userbased on the identifying information for the offline user. In oneembodiment, the online system identifies a local user having a thresholdnumber of identifiers matching the corresponding identifiers in theidentifying information of the offline user.

The online system stores the offline conversion for the identified localuser, and determines a sponsored content item of the third party systemto which the offline conversion can be attributed based on the actionindicated in the offline conversion data performed by the local user inresponse to being presented with the determined sponsored content item.In one embodiment, the online system identifies a most recent sponsoredcontent item that was presented within a range of a previous number ofdays to the identified local user during an impression opportunity, andidentifies the most recent sponsored content item as the sponsoredcontent item to be attributed to the offline conversion.

The online system transmits additional information regarding the offlineconversion to the third party system, the additional information notpreviously accessible to the third party system. In one embodiment, theonline system transmits to the third party system a conversion rate ofthe sponsored content based on a number of local users with storedoffline conversion data attributed to the sponsored content item and atotal number of local users presented with the sponsored content item.

In one embodiment, the conversion rate is further divided based on thetype of action performed by local users as indicated the stored offlineconversion data. In one embodiment, the conversion rate is furtherdivided based on the visual placement of the attributed sponsoredcontent item when the sponsored content item was presented to the localusers in the online system.

In one embodiment, the online system determines an updated bid value forthe sponsored content item based on the attribution, the updated bidvalue increased based on a value provided to the third party system bythe offline conversion.

BRIEF DESCRIPTION OF THE DRAWINGS

Figure (FIG.) 1 is a high level block diagram of a system environmentfor an online system, according to an embodiment.

FIG. 2 is an example block diagram of an architecture of the onlinesystem 140, according to an embodiment.

FIG. 3 is a transactional diagram illustrating an exemplary data flowbetween the third party system and the online system for the receipt andprocessing of offline conversion information in real-time.

FIG. 4 is a flowchart of one embodiment of a method in an online systemfor logging offline conversions in real-time.

The figures depict various embodiments of the present invention forpurposes of illustration only. One skilled in the art will readilyrecognize from the following discussion that alternative embodiments ofthe structures and methods illustrated herein may be employed withoutdeparting from the principles of the invention described herein.

DETAILED DESCRIPTION System Architecture

FIG. 1 is a high level block diagram of a system environment 100 for anonline system 140 that is able to track offline transactions inreal-time, according to an embodiment. The system environment 100 shownby FIG. 1 comprises one or more client devices 110, a network 120, oneor more third-party systems 130, and the online system 140. Inalternative configurations, different and/or additional components maybe included in the system environment 100. In one embodiment, the onlinesystem 140 is a social networking system.

The client devices 110 are one or more computing devices capable ofreceiving user input as well as transmitting and/or receiving data viathe network 120. In one embodiment, a client device 110 is aconventional computer system, such as a desktop or laptop computer.Alternatively, a client device 110 may be a device having computerfunctionality, such as a personal digital assistant (PDA), a mobiletelephone, a smartphone or another suitable device. A client device 110is configured to communicate via the network 120. In one embodiment, aclient device 110 executes an application allowing a user of the clientdevice 110 to interact with the online system 140. For example, a clientdevice 110 executes a browser application to enable interaction betweenthe client device 110 and the online system 140 via the network 120. Inanother embodiment, a client device 110 interacts with the online system140 through an application programming interface (API) running on anative operating system of the client device 110, such as IOS® orANDROID™.

The client devices 110 are configured to communicate via the network120, which may comprise any combination of local area and/or wide areanetworks, using both wired and/or wireless communication systems. In oneembodiment, the network 120 uses standard communications technologiesand/or protocols. For example, the network 120 includes communicationlinks using technologies such as Ethernet, 802.11, worldwideinteroperability for microwave access (WiMAX), 3G, 4G, code divisionmultiple access (CDMA), digital subscriber line (DSL), etc. Examples ofnetworking protocols used for communicating via the network 120 includemultiprotocol label switching (MPLS), transmission controlprotocol/Internet protocol (TCP/IP), hypertext transport protocol(HTTP), simple mail transfer protocol (SMTP), and file transfer protocol(FTP). Data exchanged over the network 120 may be represented using anysuitable format, such as hypertext markup language (HTML) or extensiblemarkup language (XML). In some embodiments, all or some of thecommunication links of the network 120 may be encrypted using anysuitable technique or techniques.

One or more third party systems 130, such as a sponsored contentprovider system, may be coupled to the network 120 for communicatingwith the online system 140, which is further described below inconjunction with FIG. 2. In one embodiment, a third party system 130 isan application provider communicating information describingapplications for execution by a client device 110 or communicating datato client devices 110 for use by an application executing on the clientdevice. In other embodiments, a third party system 130 provides contentor other information for presentation via a client device 110. A thirdparty website 130 may also communicate information to the online system140, such as advertisements, content, or information about anapplication provided by the third party website 130. Specifically, inone embodiment, a third party system 130 communicates sponsored content,such as advertisements, to the online system 140 for display to users ofthe client devices 110. The sponsored content may be created by theentity that owns the third party system 130. Such an entity may be anadvertiser or a company producing a product, service, message, orsomething else that the company wishes to promote.

For example, a third party system 130 may be an entity, such as aretailer, with physical locations. These might provide goods or servicesfor which the entity has provided information about via the onlinesystem 140. As another example, the third party system 130 may be aservices provider, such as a bank that issues credit cards, which usethe online system 140 to provide users with information regarding a typeof service, such as a credit card, and may invite those users to applyor use the services.

FIG. 2 is an example block diagram of an architecture of the onlinesystem 140, according to an embodiment. The online system 140 shown inFIG. 2 includes a user profile store 205, a content store 210, an actionlogger 215, an action log 220, an edge store 225, a sponsored contentrequest store 230, a web server 235, an offline conversions receiver240, a conversions log 250, a user identity correlator 260, anattribution calculator 270 and an offline conversions user interface(UI) module 280. In other embodiments, the online system 140 may includeadditional, fewer, or different components for various applications.Conventional components such as network interfaces, security functions,load balancers, failover servers, management and network operationsconsoles, and the like are not shown so as to not obscure the details ofthe system architecture.

Each user of the online system 140 is associated with a user profile,which is stored in the user profile store 205. A user profile includesdeclarative information about the user that was explicitly shared by theuser and may also include profile information inferred by the onlinesystem 140. In one embodiment, a user profile includes multiple datafields, each describing one or more attributes of the corresponding userof the online system 140. Examples of information stored in a userprofile include biographic, demographic, and other types of descriptiveinformation, such as work experience, educational history, gender,hobbies or preferences, location and the like. A user profile may alsostore other information provided by the user, for example, images orvideos. In certain embodiments, images of users may be tagged withidentification information of users of the online system 140 displayedin an image. A user profile in the user profile store 205 may alsomaintain references to actions by the corresponding user performed oncontent items in the content store 210 and stored in the action log 220.

While user profiles in the user profile store 205 are frequentlyassociated with individuals, allowing individuals to interact with eachother via the online system 140, user profiles may also be stored forentities such as businesses or organizations. This allows an entity toestablish a presence on the online system 140 for connecting andexchanging content with other online system users. The entity may postinformation about itself, about its products or provide otherinformation to users of the online system using a brand page associatedwith the entity's user profile. Other users of the online system mayconnect to the brand page to receive information posted to the brandpage or to receive information from the brand page. A user profileassociated with the brand page may include information about the entityitself, providing users with background or informational data about theentity.

The content store 210 stores objects that each represent various typesof content. Examples of content represented by an object include a pagepost, a status update, a photograph, a video, a link, a shared contentitem, a gaming application achievement, a check-in event at a localbusiness, a brand page, or any other type of content. Online systemusers may create objects stored by the content store 210, such as statusupdates, photos tagged by users to be associated with other objects inthe online system, events, groups or applications. In some embodiments,objects are received from third-party applications or third-partyapplications separate from the online system 140. In one embodiment,objects in the content store 210 represent single pieces of content, orcontent “items.” Hence, users of the online system 140 are encouraged tocommunicate with each other by posting text and content items of varioustypes of media through various communication channels. This increasesthe amount of interaction of users with each other and increases thefrequency with which users interact within the online system 140.

The action logger 215 receives communications about user actionsinternal to and/or external to the online system 140, populating theaction log 220 with information about user actions. Examples of actionsinclude adding a connection to another user, sending a message toanother user, uploading an image, reading a message from another user,viewing content associated with another user, attending an event postedby another user, among others. In addition, a number of actions mayinvolve an object and one or more particular users, so these actions areassociated with those users as well and stored in the action log 220.

The action log 220 may be used by the online system 140 to track useractions on the online system 140, as well as actions on third partysystems 130 that communicate information to the online system 140. Usersmay interact with various objects on the online system 140, andinformation describing these interactions are stored in the action log210. Examples of interactions with objects include: commenting on posts,sharing links, and checking-in to physical locations via a mobiledevice, accessing content items, and any other interactions. Additionalexamples of interactions with objects on the online system 140 that areincluded in the action log 220 include: commenting on a photo album,communicating with a user, establishing a connection with an object,joining an event to a calendar, joining a group, creating an event,authorizing an application, using an application, expressing apreference for an object (“liking” the object) and engaging in atransaction. Additionally, the action log 220 may record a user'sinteractions with advertisements on the online system 140 as well aswith other applications operating on the online system 140. In someembodiments, data from the action log 220 is used to infer interests orpreferences of a user, augmenting the interests included in the user'suser profile and allowing a more complete understanding of userpreferences.

The action log 220 may also store user actions taken on a third partysystem 130, such as an external website, and communicated to the onlinesystem 140. For example, an e-commerce website that primarily sellssporting equipment at bargain prices may recognize a user of an onlinesystem 140 through a social plug-in enabling the e-commerce website toidentify the user of the online system 140. Because users of the onlinesystem 140 are uniquely identifiable, e-commerce websites, such as thissporting equipment retailer, may communicate information about a user'sactions outside of the online system 140 to the online system 140 forassociation with the user. Hence, the action log 220 may recordinformation about actions users perform on a third party system 130,including webpage viewing histories, advertisements that were engaged,purchases made, and other patterns from shopping and buying.

In one embodiment, an edge store 225 stores information describingconnections between users and other objects on the online system 140 asedges. Some edges may be defined by users, allowing users to specifytheir relationships with other users. For example, users may generateedges with other users that parallel the users' real-life relationships,such as friends, co-workers, partners, and so forth. Other edges aregenerated when users interact with objects in the online system 140,such as expressing interest in a page on the online system, sharing alink with other users of the online system, and commenting on posts madeby other users of the online system.

In one embodiment, an edge may include various features eachrepresenting characteristics of interactions between users, interactionsbetween users and object, or interactions between objects. For example,features included in an edge describe rate of interaction between twousers, how recently two users have interacted with each other, the rateor amount of information retrieved by one user about an object, or thenumber and types of comments posted by a user about an object. Thefeatures may also represent information describing a particular objector user. For example, a feature may represent the level of interest thata user has in a particular topic, the rate at which the user logs intothe online system 140, or information describing demographic informationabout a user. Each feature may be associated with a source object oruser, a target object or user, and a feature value. A feature may bespecified as an expression based on values describing the source objector user, the target object or user, or interactions between the sourceobject or user and target object or user; hence, an edge may berepresented as one or more feature expressions.

The edge store 225 also stores information about edges, such as affinityscores for objects, interests, and other users. Affinity scores, or“affinities,” may be computed by the online system 140 over time toapproximate a user's affinity for an object, interest, and other usersin the online system 140 based on the actions performed by the user. Auser's affinity may be computed by the online system 140 over time toapproximate a user's affinity for an object, interest, and other usersin the online system 140 based on the actions performed by the user.Computation of affinity is further described in U.S. patent applicationSer. No. 12/978,265, filed on Dec. 23, 2010, U.S. patent applicationSer. No. 13/690,254, filed on Nov. 30, 2012, U.S. patent applicationSer. No. 13/689,969, filed on Nov. 30, 2012, and U.S. patent applicationSer. No. 13/690,088, filed on Nov. 30, 2012, each of which is herebyincorporated by reference in its entirety. Multiple interactions betweena user and a specific object may be stored as a single edge in the edgestore 225, in one embodiment. Alternatively, each interaction between auser and a specific object is stored as a separate edge. In someembodiments, connections between users may be stored in the user profilestore 205, or the user profile store 205 may access the edge store 225to determine connections between users.

The sponsored content request store 230 stores one or more sponsoredcontent requests. Sponsored content is content that an entity (i.e., asponsored content provider) presents to users of an online system andallows the sponsored content provider to gain public attention forproducts, services, opinions, causes, or messages and to persuade onlinesystem users to take an action regarding the entity's products,services, opinions, or causes. In one embodiment, a sponsored contentitem is an advertisement, and the sponsored content request store 230stores advertisement requests (“ad requests”). An ad request includesadvertisement content, also referred to as an “advertisement” and a bidamount. The advertisement content is text, image, audio, video, or anyother suitable data presented to a user. In various embodiments, theadvertisement content also includes a landing page specifying a networkaddress to which a user is directed when the advertisement is accessed.The bid amount is associated with an ad request by an advertiser (whomay be the entity providing the sponsored content) and is used todetermine an expected value, such as monetary compensation, provided byan advertiser to the online system 140 if advertisement content in thead request is presented to a user, if the advertisement content in thead request receives a user interaction when presented, or if anysuitable condition is satisfied when advertisement content in the adrequest is presented to a user. For example, the bid amount specifies oris used to compute a monetary amount that the online system 140 receivesfrom the advertiser if advertisement content in an ad request isdisplayed. In some embodiments, the expected value to the online system140 of presenting the advertisement content may be determined bymultiplying the bid amount by a probability of the advertisement contentbeing accessed by a user.

Additionally, an advertisement request may include one or more targetingcriteria specified by the advertiser. Targeting criteria included in anadvertisement request specify one or more characteristics of userseligible to be presented with advertisement content in the advertisementrequest. For example, targeting criteria are used to identify usershaving user profile information, edges, or actions satisfying at leastone of the targeting criteria. Hence, targeting criteria allow anadvertiser to identify users having specific characteristics,simplifying subsequent distribution of content to different users.

In one embodiment, targeting criteria may specify actions or types ofconnections between a user and another user or object of the onlinesystem 140. Targeting criteria may also specify interactions between auser and objects performed external to the online system 140, such as ona third party system 130. For example, targeting criteria identifiesusers that have taken a particular action, such as sent a message toanother user, used an application, joined a group, left a group, joinedan event, generated an event description, purchased or reviewed aproduct or service using an online marketplace, requested informationfrom a third party system 130, installed an application, or performedany other suitable action. Including actions in targeting criteriaallows advertisers to further refine users eligible to be presented withadvertisement content from an advertisement request. As another example,targeting criteria identifies users having a connection to another useror object or having a particular type of connection to another user orobject.

The web server 235 links the online system 140 via the network 120 tothe one or more client devices 110, as well as to the one or more thirdparty systems 130. The web server 235 serves web pages, as well as otherweb-related content, such as JAVA®, FLASH®, XML and so forth. The webserver 235 may receive and route messages between the online system 140and the client device 110, for example, instant messages, queuedmessages (e.g., email), text messages, short message service (SMS)messages, or messages sent using any other suitable messaging technique.A user may send a request to the web server 245 to upload information(e.g., images or videos) that are stored in the content store 210.Additionally, the web server 235 may provide application programminginterface (API) functionality to send data directly to native clientdevice operating systems, such as IOS®, ANDROID™, WEBOS® or RIM®.

The offline conversions receiver 240 receives, e.g., as in step 405 ofFIG. 4, offline conversions information from the third party systems130. As used here, offline conversions refers to actions, such astransactions, performed by users with regards to the third party systems130 but which are not directly trackable by the online system 140. Theseactions performed by users may provide some benefit to the third partysystem 130, i.e., the actions provide a value (e.g., an increase inrevenue, a desired action) to the third party system 130, and may beperformed in response to being presented with content (e.g., sponsoredcontent) from the third party system 130 at the online system 140. Theaction may not be directly trackable by the online system 140 becausethe action is performed in a scenario where the performance of theaction does not result in an immediate message or other data being sentto the online system 140. As an example, in a trackable case, the actionperformed may be a purchase at the website of the third party system130. When the user (i.e., the client device 110 of the user) requeststhe web page where the purchase is completed (e.g., an orderconfirmation page), the web page may include a tracking pixel or othermechanism that transmits a message to the online system 140 indicatingthat the action was performed.

However, in the case of an action that is not directly trackable, suchautomated means of tracking the action performed (e.g., via a website)is not available. Examples of such actions may include completing atransaction at a physical retail location, completing a transaction madeonline at a physical location (e.g., a convenience store), successfullyaccepting a services transaction (e.g., a credit card application) aftera user has initiated the transaction, completing a transaction at anintermediary not directly linked to the third party system 130 (e.g., amarketplace website).

In these and other similar cases, the offline conversions receiver 240may provide a separate method for the third party system 130 to transmitinformation regarding these offline conversions to the online system140.

The offline conversions receiver 240 may provide the third party system130 with a variety of options to transmit the offline conversions data.For example, the offline conversions receiver 240 may provide anapplication programming interface (API), user interface, standard fileformat definition, or other option(s) to the third party system 130 toallow the third party system 130 to transmit the offline conversionsdata to the online system 130 to be received by the offline conversionsreceiver 240. In one embodiment, the options provided to the third partysystem 130 allow the third party system 130 to send the offlineconversions data in real-time, i.e., as the actions of the offlineconversions are completed, or immediately after the third party system130 considers the actions to be completed (e.g., in the case of anaction such as retail purchase, the action may be completed once agrace/return period is ended). Each use of the term “real-time” hereinmeans as an action happens or substantially immediately thereafter.However, in alternative embodiments, the offline conversions receiver240 may also receive the information in batch (e.g., at a later time, orperiodically, but not necessarily in real time).

For each offline conversion, the offline conversions receiver 240 mayreceive from a third party system 130 an indication of the type ofaction performed, the identity of the offline user (which may be hashedor non-hashed, and may include personally identifiable or non-personallyidentifiable information), the timestamp of the action, and othermetadata such as the revenue/profit generated by the action, a valuescore of the action to the third party system 130, and so on. Theoffline conversions receiver 240 may store this offline conversionsinformation in the conversions log 250.

The user identity correlator 260 identifies, e.g., as in step 410 ofFIG. 4, the local user of the online system 140 corresponding to anoffline user identified in an instance of offline conversions datareceived from the third party system 130 regarding a particular actionperformed by the offline user. Each entry of the offline conversionsdata may identify an offline user that performed the action indicated inthe offline conversions data. The user identity correlator 260determines whether this identified offline user is the same as a localuser of the online system 140, and if so, indicates the association orcorrelation between the matched local user and the identified offlineuser.

The online system 140 may receive from the third party system 130various identifiers for the offline user, and depending on the thirdparty system 130, these identifiers may be different, and include moreor less information. The identifiers may also be hashed to preventleakage of personally identifiable information (i.e., the receivedinformation is hashed so that the online system 140 only knows theidentity of the offline user if the hash matches a hash of the sameidentifiers for a local user).

The user identity correlator 260 searches the local users of the onlinesystem 140 (e.g., users in the user profile store 205) to determinewhether a local user exists that matches the information provided forthe offline user. The user identity correlator 260 may attempt to matchthe identifiers provided for the offline user with the local users ofthe online system 140 until a match is found where all (or a percentage)of the information provided for the offline user matches the informationof the local user. The user identity correlator 260 may assign aconfidence score or measure of accuracy indicating the reliability ofthe match, i.e., whether the match is a true match or whether the localuser may not actually be the same as the offline user. Subsequently,only those matches with scores above a threshold value may be consideredfor use in determining attribution and conversion rates. In other words,not all the information provided for the offline user may have tocompletely match a local user for a match to be positive.

Additional details regarding matching local users with identifiers ofusers provided by third party systems are described in U.S. Pat. Pub.No. 2014/0257999, filed Mar. 7, 2013, U.S. Pat. Pub. No. 2013/0138569,filed Nov. 29, 2011, and U.S. Pat. Pub. No. 2016/0078134, filed Sep. 16,2014, all of which are incorporated by reference herein in theirentirety.

Once the user identity correlator 260 determines that a local usermatches an offline user, the user identity correlator 260 may store theassociation in the conversions log 250 for the corresponding offlineconversions data entry, e.g., as in step 415 of FIG. 4. The useridentity correlator 260 may perform the above matching operations inreal time as the offline conversions data is received from the thirdparty systems 130.

The conversions log 250 stores the offline conversions informationreceived by the offline conversions receiver 240. For each third partysystem 130, the conversions log 250 may store separate offlineconversions information. For example, each entry in the conversions logmay correspond to one offline conversion event and may includeindications of the third party system 130, the action performed (e.g.,retail purchase, credit application approved, etc.), a timestamp for theaction, identifying information for the offline user that performed theaction, an indication of the local user that matches the offline user,and any other metadata related to the entry, such as revenue generated,a value score of the action to the third party system 130, and so on.This data may later be used to determine the attribution for the offlineconversion, as well as the conversion rate of users presented with aparticular piece of content from the third party system, among otherinformation. The conversion rate for a particular content from a thirdparty system 130 refers to the rate at which users perform actions, bothdirectly trackable and not directly trackable, after being presentedwith the particular content (e.g., sponsored content).

The attributions calculator 270 computes the attribution of a sponsoredcontent item presented to the local users of the online system 140 incausing the actions indicated in the offline conversions data. Theattribution of a sponsored content item to an offline conversionindicates the sponsored content has most likely contributed to the localuser performing the action in the offline conversion. In other words,the attribution indicates which sponsored content, if any, presented toa local user is most correlated with the local user performing theaction. In some cases, each action may also be attributed to multipleprior presentations of sponsored content (which may have been presentedon different types of devices, and may have been reacted to differentlyby users). If multiple prior presentations are attributed, eachpresentation may receive an attribution value indicating the portion ofthe attribution allocated to that presentation.

By receiving the data for the offline conversions for a third partysystem 130 in real-time (or near real-time), the attributions calculator270 is able to determine the attribution effects of the offlineconversion and update future estimated bid values for content from thesame third party system 130, as well as present the attributioninformation to the third party system 130.

For each third party system 130, and for each sponsored content that thethird party system 130 may have requested the online system 140 topresent to local users, the attributions calculator 270 may determine,e.g., as in step 420 of FIG. 4, an attribution value for the sponsoredcontent indicating the attribution for that sponsored content in causingthe action by an offline user (that is matched to a local user). Theattributions calculator 270 retrieves the information regarding thethird party system 130 from the conversions log 250 indicating theoffline conversions for the third party system 130. The attributionscalculator 270 also retrieves the information regarding the presentationof sponsored content from the third party system 130 to local users ofthe online system 140. This information may be stored in the action log220.

Using this information, the attributions calculator 270 may determine(in real-time or periodically) which presentations of the sponsoredcontent should be attributed to each offline conversion entry retrievedfrom the conversions log 250 for the third party system. Theattributions calculator 270 may identify the most recent sponsoredcontent from the corresponding third party system 130 that was presentedin an impression opportunity (e.g., up to 28 days back) to a local userindicated in an offline conversion entry. The attributions calculatormay then attribute the offline conversion to that most recent sponsoredcontent. Alternatively, the attributions calculator 270 may attributethe offline conversion to multiple presentations of sponsored contentfrom the third party system 130 in a time-weighted fashion such that themost recently presented sponsored content receives a higher attributionpercentage (e.g., a multi-touch attribution). For example, theattribution percentage of a sponsored content item may decreaseinversely as a square of the time difference between the presentation ofthe sponsored content and the occurrence of the offline conversion.

The attributions calculator 270 may also maintain separate attributioninformation depending upon the type of response the offline user madeagainst the sponsored content. The offline user may have only viewed thesponsored content, or may have clicked on it, posted about it, commentedabout it, and so on. The attributions calculator 270 may indicate witheach attribution which one of these types of responses was made by theoffline user.

The attributions calculator 270 may also compute an updated bid valuebased on the offline conversions data. The attribution information thatis computed as described above allows the attributions calculator 270 todetermine which types of sponsored content, presented at which points intime, on which client devices (e.g., mobile vs desktop), to which users(with certain characteristics), produce the highest chances, or highestvalue, in offline conversions. The attributions calculator 270 maymodify the bid values for these sponsored content items when animpression opportunity arises for a local user. The attributionscalculator 270 may increase the bid value when presenting the sponsoredcontent for the third party system 130 is favorable, and may decreasethe bid value if not favorable. For example, the attributions calculator270 may determine that local users in a particular geographic region arehighly likely to perform an offline conversion due to presentation of aparticular sponsored content from a third party system 130, as shown bythe computed attribution data. The attributions calculator 270 mayincrease the bid value (up to a maximum that may be specified by thethird party system 130) for that sponsored content to increase thechances of winning the bid.

The increased bid value may be determined by the attributions calculator270 based on a computation of the number of presentations of thesponsored content for every offline conversion, i.e., the conversionrate. As the offline conversion brings in a certain amount of value orprofit (e.g., a retail store purchase brings in a profit), and as thebid costs money, the attributions calculator 270 may determine a bidvalue such that on average, a certain profit margin is maintained inconsideration of these factors. The attributions calculator 270 mayfurther determine a separate bid value for each type of response (e.g.,view only, click, etc.) made by a user against a sponsored content itemin a similar fashion.

In some cases, when determining the conversion rate, the attributionscalculator 270 may account for reversed actions as indicated the thirdparty system 130 in the offline conversions data. A reversed action mayoccur when a transaction is reversed, such as in the case of a refund.The reversed action may count as negative and decrease the conversionrate.

Additional details regarding determining attribution may be found inU.S. Pat. Pub. No. 2016/0027040, filed Jul. 25, 2014, and which ishereby incorporated by reference in its entirety.

In other embodiments, the online system 140 uses the offline conversionsdata (with matched local user information) to generate targetingclusters of users. These targeting clusters of users may be used by theonline system 140 to provide third party systems 130 with a group ofusers that are more likely to generate value for the third party system130. Additional details regarding the generation of targeting clustersis described in U.S. Pat. Pub. No. 2015/0088663, filed Sep. 23, 2013,and U.S. Pat. Pub. No. 2015/0227977, filed Feb. 11, 2014, both of whichare hereby incorporated by reference in their entirety.

The offline conversions user interface (UI) module 280 presentsinformation about the offline conversions to the third party systems130. The offline conversions UI module 280 may allow each third partysystem 130 to see the conversion rate of each sponsored content itemprovided by the third party system 130. In other words, the offlineconversions UI module 280 may present to the third party system 130 theeffectiveness of each sponsored content item. The offline conversions UImodule 280 may compute the conversion rate by dividing the number ofstored offline conversion entries for a sponsored content item by thetotal number of impressions of that sponsored content item. The offlineconversions UI module 280 may also present to the third party system 130information regarding the attributions for different types of offlineconversions, i.e., which sponsored content causes which types of actionsin the offline conversions, e.g., as described in step 420 of FIG. 4

The offline conversions UI module 280 may present to the third partysystem 130 regarding how the placement of the sponsored content (e.g.,within a news feed, on a side bar, etc.) within the web page or othermedium may affect the attribution and/or conversion rates for offlineconversions. To compute a conversion rate for a sponsored content item,the offline conversions UI module 280 determines the number ofpresentations made for the sponsored content compared to the number ofoffline conversion events attributed to the same sponsored content.

The offline conversions UI module 280 may present to the third partysystem 130 an identifier of the client device on which the local userwas presented with the sponsored content that is attributed to theoffline conversion. The offline conversions UI module 280 may alsoindicate what portions (e.g., percentages) of the attributions werebased on what type of response against the sponsored content item (e.g.,view, click, etc.).

To present the information described above, the offline conversions UImodule 280 may categorize each type of sponsored content, eachpresentation of the sponsored content, and so on, into separate bins,compute the statistics (e.g., conversion rate) separately for each bin,and present each bin separately to the third party system 130. Forexample, the offline conversions UI module 280 may bin the offlineconversions associated with different placements of the same sponsoredcontent separately, and present the statistics regarding these binsseparately.

The offline conversions UI module 280 may also present details regardingeach offline conversion, including the type of the offline conversion(e.g., retail purchase, deferred payment), the sponsored contentattributed to it, as well as other details regarding the sponsoredcontent and the offline conversion, such as those factors describedabove (e.g., content placement). As a result of this new information,the third party system 130 is able to see additional informationregarding the effect of sponsored content presented to local users ofthe online system 140 for offline conversions.

Additional details regarding the system described above are presentedbelow with regards to FIGS. 3-4.

As noted above, the system as described here has many advantagescompared to a traditional method. Previously, a system may not have beeneasily able to determine the effects of offline conversions. At most, asystem may have performed a simple lift analysis much later on, andafter the fact, to determine in the aggregate an approximate effect onoffline conversions. However, without being able to provide informationregarding the effects of offline conversions in a timely fashion, theinformation is not significantly useful to a third party system 130.

Instead, as described here, by providing the information in (near)real-time, the third party systems 130 may quickly adjust for and reactto the changes in user response to sponsored content. Furthermore, asdescribed in further detail below, the receipt of offline conversionsinformation allows for more accurate tracking of users' actions, basedon an actual occurrence of the action, rather than an estimation orguess that the action may have occurred.

For example, in the case of deferred payments, a user may have reached apayment instruction web page requesting the user to remit payment to aparticular bank account. If the online system 140 were to track theuser's actions only up to this web page, the information gathered by theonline system 140 may not be accurate, as many users may not actuallytransfer payment subsequently to the particular bank account. Instead,by receiving the offline conversion information regarding payments tothe bank account from the third party system 130, the online system 140is able to gather much more accurate information regarding userbehavior, and pass this information back to the third party system 130.

Exemplary Transactional Diagram Illustrating the Receipt and Processingof Offline Conversion Information by an Online System

FIG. 3 is a transactional diagram illustrating an exemplary data flowbetween the third party system 130 and the online system 140 for thereceipt and processing of offline conversion information in real-time.Although certain elements are illustrated in FIG. 3, in otherembodiments the elements may be different and the flow of the datathrough the elements may be different.

At some prior point in time, the online system 140 may have presented305 content from the third party system in an impression opportunity toa target user, who is a local user of the online system 140. The targetuser may have responded to the content by viewing it, clicking on it,interacting with it, etc., as described above.

Subsequently, a user of the third party system 130 makes 310 an offlineconversion. These offline conversions may include different types ofactions which are not directly trackable, as described above. Someexamples of these actions are presented in FIG. 3 and described below,however, such actions are not limited to these examples.

The action may be a transaction 315A made in a delayed transactionservice. After viewing a sponsored content item, a target user may visitthe website of a third party system 130 that supports a delayed paymentservice. Such a service allows a user to indicate a purchase for somegoods or services online at the third party system 130. Subsequently,the third party system 130 provides the user the option to submitpayment for the purchase through an offline means, at which point thetransaction is completed and the goods or services is to be provided.For example, a target user may purchase an item at the website of athird party system 130. At the payment web page of the third partysystem 130, the target user is provided by the third party system 130with the option to submit a payment offline. This might be by providinga bank wire transfer number, bank account number, by providing a paymentcertificate, or other identifier of an offline payment method. Thetarget user may complete the transaction by submitting the paymentoffline, such as by sending the payment to the specified bank wire oraccount number, or bringing the payment certificate to a local bank orother physical merchant in the payment certificate network, and payingfor the purchase at that point (e.g., handing over the paymentcertificate and purchase amount to a store clerk). Such offline paymentmethods would not be directly trackable.

The action may be a transaction 315B made at a physical location. Afterviewing a sponsored content item from the third party system 130 at theonline system 140, the target user may visit a physical location (e.g.,a physical retail store) of the third party system 130 and purchase anitem at that location. For example, a sponsored content item presentedto the target user may be of some clothing item or other product. Thetarget user may wish to test or try the product at a physical storebefore purchasing it. Upon testing the item, the target user maypurchase the item in store. Such physical transactions would not bedirectly trackable by the online system 140.

The action may be a services transaction 315C that is subsequentlyaccepted. In some cases, a target user may be presented with sponsoredcontent from the third party system 130 inviting the user to apply foror submit to an approval or other process before the transaction isconsidered complete. An example of this is for acquiring a credit card.A target user is requested to complete the credit card application andreceive an approval before the transaction is completed and the user isissued a credit card. The approval of the user is an action that is notdirectly trackable either. Another example of such a transaction may bea periodic payment transaction, where the benefit to the third partysystem 130 is counted when a threshold number of payments have beenmade.

The action may be a transaction 315D performed at an intermediary. Insome cases, the target user may not make the transaction at the thirdparty system 130, but instead may transact the third party system'sgoods or services at an intermediary. For example, a target user may usea travel agency to book a ticket for an airliner, or may use amarketplace website to purchase a company's product. Such a transactionmay not be directly trackable since the intermediary may not have adirect relationship with the online system 140, and so no trackingmechanism is implemented at the intermediary.

As described above, these offline conversions may be common occurrences,but cannot be directly (or easily) tracked using common means. Instead,as described above with regards to FIG. 2, the online system 140 mayprovide the third party system 130 with various tools (e.g., an API) tosend the information regarding the offline conversions to the onlinesystem 140 to allow for real-time tracking of these offline conversions.

Thus, after the offline conversion occurs, the third party system 130may record 320 the offline conversion for an offline user. This offlineuser is a user who performed a transaction or other action not directlytrackable by the online system, and who may the same target userdescribed above. Subsequently, the third party system 130 sends 325 theoffline conversion information as a message(s) 330 to the online system140 (which may be in real-time). The offline conversion information sentto the online system 140 may include a description of the actionperformed (e.g., a retail purchase), an identifier of the offline user(e.g., publicly available information, a unique identifier, a hash of apersonally identifiable information, etc.), a timestamp of the when theaction occurred, and possibly other metadata regarding the action, suchas the dollar amount of any transactions, and so on.

The online system 140 (e.g., the offline conversions receiver 240)receives the message(s) 330 that have the offline conversion information(e.g., as described in step 405 of FIG. 4). Using the identifier of theoffline user, the online system 140 (e.g., the user identity correlator260) attempts to match 335 the offline user with a local user of theonline system 140, as described above. The online system 140 maydetermine 340 may determine that the offline user matches the targetuser to whom content from the third party system 130 was previouslypresented (e.g., as described in step 410 of FIG. 4). Thus, the user whoperformed the action in the offline conversion is the same user to whomthe online system 140 previously targeted to present a sponsored contentitem from the third party system 130. The online system 140 may storethis association as well as the offline conversion information (e.g., asdescribed in step 415 of FIG. 4).

The online system 140 (e.g., the attribution calculator 270) may thendetermine 345 the attribution of the offline conversion for the localuser (e.g., as described in step 420 of FIG. 4). As described above, theonline system 140 may determine the attribution by determining the mostrecent sponsored content item that was presented to the target user andattributing the offline conversion to the presentation of the recentsponsored content. The online system 140 may store this attributioninformation as well (e.g., in the conversions log 250).

The online system 140 may update 350 the conversion information for thethird party system 130 in real-time based on the offline conversioninformation received from the third party system (e.g., as described instep 425 of FIG. 4). This may include presenting the updated conversionand attribution information to the third party system 130 via a UI, orby updating the bids for the sponsored content of the third party system130 as described above. The online system 140 may also update theinformation through other means, such as an API.

Exemplary Flow of a Method of Logging Offline Conversions in Real-Time

FIG. 4 is a flowchart of one embodiment of a method in an online systemfor logging offline conversions in real-time. In other embodiments, themethod may include different and/or additional steps than thosedescribed in conjunction with FIG. 4. Additionally, in some embodiments,the method may perform the steps described in conjunction with FIG. 4 indifferent orders. In one embodiment, the method is performed by one ormore of the modules of the online system 140 described above.

The online system 140 (e.g., the offline conversions receiver 240)receives 405 offline conversions data from a third party system inreal-time for an offline user. As noted, an offline user is a user whoperformed an action in an offline conversion, such as making a paymentvia a delayed payment service, making a purchase at a retail physicallocation, being approved for a services transaction, or making apurchase through an intermediary. The offline conversion refers toinformation about an action performed by a user, and which in some casesmay be as a result of the user being presented with a sponsored contentitem from the third party system, and which is not directly trackable bythe online system 140.

The online system 140 (e.g., the user identity correlator 260)identifies 410 a local user that matches the offline user usinginformation from received offline conversion data. The offlineconversions data may include information such as zip codes, phonenumber, and so on, that may be used to identify the offline user. Asnoted above, the online system 140 may attempt to match this informationwith the information it has about local users in order to find a match.

The online system 140 (e.g., the user identity correlator 260) stores415 the offline conversion for the local user. Since the online system140 was able to find a match with a local user, the online system 140may store the offline conversion information locally (e.g., in theconversions log 250).

The online system 140 (e.g., the attribution calculator 270) determines420 the attribution for the offline conversion for the local user. Theonline system 140 may look up prior presentations of sponsored contentto the local user from the third party system associated with theoffline conversion to determine whether the local user was presentedwith sponsored content from the third party system. If a presentation ofsponsored content is found, the online system 140 may attribute theoffline conversion to this presentation of sponsored content. Asdescribed above, the online system 140 may also modify the bid values ofthe sponsored content based on the attribution information.

The online system 140 (e.g., the offline conversions UI module 280)presents 425 the updated conversion information to the third partysystem in real-time. This updated conversion information is informationthat is not available to the third party system, or includes additionalinformation about the offline conversions. As described above, thisinformation may include various statistics regarding the attribution,conversion rates, metadata, and other information regarding the offlineconversions, the local users who performed actions indicated in theoffline conversions, the sponsored content attributed to the offlineconversions, and so on. As the online system 140 may update thisinformation in real-time (or near real-time), the third party system 130(or an administrator of the third party system 130) can react quickly toa situation that may adversely affect the third party system 130.

SUMMARY

The foregoing description of the embodiments of the invention has beenpresented for the purpose of illustration; it is not intended to beexhaustive or to limit the invention to the precise forms disclosed.Persons skilled in the relevant art can appreciate that manymodifications and variations are possible in light of the abovedisclosure.

Some portions of this description describe the embodiments of theinvention in terms of algorithms and symbolic representations ofoperations on information. These algorithmic descriptions andrepresentations are commonly used by those skilled in the dataprocessing arts to convey the substance of their work effectively toothers skilled in the art. These operations, while describedfunctionally, computationally, or logically, are understood to beimplemented by computer programs or equivalent electrical circuits,microcode, or the like. Furthermore, it has also proven convenient attimes, to refer to these arrangements of operations as modules, withoutloss of generality. The described operations and their associatedmodules may be embodied in software, firmware, hardware, or anycombinations thereof.

Any of the steps, operations, or processes described herein may beperformed or implemented with one or more hardware or software modules,alone or in combination with other devices. In one embodiment, asoftware module is implemented with a computer program productcomprising a computer-readable medium containing computer program code,which can be executed by a computer processor for performing any or allof the steps, operations, or processes described.

Embodiments of the invention may also relate to an apparatus forperforming the operations herein. This apparatus may be speciallyconstructed for the required purposes, and/or it may comprise ageneral-purpose computing device selectively activated or reconfiguredby a computer program stored in the computer. Such a computer programmay be stored in a non-transitory, tangible computer readable storagemedium, or any type of media suitable for storing electronicinstructions, which may be coupled to a computer system any computingsystems referred to in the specification may include a single processoror may be architectures employing multiple processor designs forincreased computing capability.

Embodiments of the invention may also relate to a product that isproduced by a computing process described herein. Such a product maycomprise information resulting from a computing process, where theinformation is stored on a non-transitory, tangible computer readablestorage medium and may include any embodiment of a computer programproduct or other data combination described herein.

Finally, the language used in the specification has been principallyselected for readability and instructional purposes, and it may not havebeen selected to delineate or circumscribe the inventive subject matter.It is therefore intended that the scope of the invention be limited notby this detailed description, but rather by any claims that issue on anapplication based hereon. Accordingly, the disclosure of the embodimentsof the invention is intended to be illustrative, but not limiting, ofthe scope of the invention, which is set forth in the following claims.

1-20. (canceled)
 21. A system, comprising: a processor; and a memorystoring instructions, which when executed by the processor, cause theprocessor to: receiving, from a third party system, a message comprisinginstructions to add offline conversion data for an offline user, whereinthe offline conversion data comprises an indication of an actionperformed by the offline user that is not directly trackable, and theoffline conversion data is added to communications between an onlinesystem and the third party system and received in real-time as theactions of the offline conversions are completed; identifying a localuser matching the offline user by matching identifying information ofthe local user with the identifying information of the offline userreceived in offline conversion data entry from the message, wherein thematching is based on: assigning a confidence score to a match betweenthe local user and the offline user, and determining whether theconfidence score meets a predetermined threshold; identifying one ormore sponsored content items of the third party system that werepresented within a range of a previous time period to the identifiedlocal user during one or more impression opportunities at the onlinesystem; and determining an attribution amount of the offline conversionfor each of the one or more sponsored content items that is inverselyproportional to the time between a timestamp of the impressionopportunity of the sponsored content item and a timestamp of anoccurrence of the offline conversion.
 22. The system of claim 21,further comprising: computing an updated bid value for each of the oneor more sponsored content items for the identified local user, whereinthe updated bid value is increased or decreased based on correspondingattribution amounts for that sponsored content item, and wherein theupdated bid value is computed by the online system when submitting thesponsored content item for impression opportunities for the identifiedlocal user.
 23. The system of claim 21, further comprising: transmittinginstructions to a client device associated with the third party systemto cause the client device to display a user interface presentingadditional information regarding the offline conversion to the thirdparty system, wherein the additional information comprises a conversionrate of the one or more sponsored content items computed using storedoffline conversion data, and wherein the additional information was notpreviously accessible to the third party system.
 24. The system of claim23, wherein the transmitting instructions to present additionalinformation regarding the offline conversion further comprises:transmitting, to the third party system, a conversion rate of thesponsored content based on a number of local users with stored offlineconversion data attributed to the sponsored content item and a totalnumber of local users presented with the sponsored content item.
 25. Thesystem of claim 24, wherein the conversion rate is based on at least onetype of action performed by offline users as indicated by the storedoffline conversion data.
 26. The system of claim 24, wherein theconversion rate is based on visual placement of the attributed sponsoredcontent item when the sponsored content item was presented to the localusers in the online system.
 27. The system of claim 21, wherein theaction is not directly trackable by the online system via a website ofthe third party system, and wherein the action comprises at least oneof: a transaction at a physical location, a transaction as part of adelayed payment service, a transaction as part of a service approvalprocess, or a transaction completed at an intermediary.
 28. A method,comprising: receiving, from a third party system, a message comprisinginstructions to add offline conversion data for an offline user, whereinthe offline conversion data comprises an indication of an actionperformed by the offline user that is not directly trackable, and theoffline conversion data is added to communications between an onlinesystem and the third party system and received in real-time as theactions of the offline conversions are completed; identifying a localuser matching the offline user by matching identifying information ofthe local user with the identifying information of the offline userreceived in offline conversion data entry from the message, wherein thematching is based on: assigning a confidence score to a match betweenthe local user and the offline user, and determining whether theconfidence score meets a predetermined threshold; identifying one ormore sponsored content items of the third party system that werepresented within a range of a previous time period to the identifiedlocal user during one or more impression opportunities at the onlinesystem; and determining an attribution amount of the offline conversionfor each of the one or more sponsored content items that is inverselyproportional to the time between a timestamp of the impressionopportunity of the sponsored content item and a timestamp of anoccurrence of the offline conversion.
 29. The method of claim 28,further comprising: computing an updated bid value for each of the oneor more sponsored content items for the identified local user, whereinthe updated bid value is increased or decreased based on correspondingattribution amounts for that sponsored content item, and wherein theupdated bid value is computed by the online system when submitting thesponsored content item for impression opportunities for the identifiedlocal user.
 30. The method of claim 28, further comprising: transmittinginstructions to a client device associated with the third party systemto cause the client device to display a user interface presentingadditional information regarding the offline conversion to the thirdparty system, wherein the additional information comprises a conversionrate of the one or more sponsored content items computed using storedoffline conversion data, and wherein the additional information was notpreviously accessible to the third party system.
 31. The method of claim30, wherein the transmitting instructions to present additionalinformation regarding the offline conversion further comprises:transmitting, to the third party system, a conversion rate of thesponsored content based on a number of local users with stored offlineconversion data attributed to the sponsored content item and a totalnumber of local users presented with the sponsored content item.
 32. Themethod of claim 31, wherein the conversion rate is based on at least oneof: type of action performed by offline users as indicated by the storedoffline conversion data; or visual placement of the attributed sponsoredcontent item when the sponsored content item was presented to the localusers in the online system.
 33. The method of claim 28, wherein theaction is not directly trackable by the online system via a website ofthe third party system, and wherein the action comprises at least oneof: a transaction at a physical location, a transaction as part of adelayed payment service, a transaction as part of a service approvalprocess, or a transaction completed at an intermediary.
 34. Anon-transitory computer-readable storage medium having an executablestored thereon, which when executed instructs a processor to: receiving,from a third party system, a message comprising instructions to addoffline conversion data for an offline user, wherein the offlineconversion data comprises an indication of an action performed by theoffline user that is not directly trackable, and the offline conversiondata is added to communications between an online system and the thirdparty system and received in real-time as the actions of the offlineconversions are completed; identifying a local user matching the offlineuser by matching identifying information of the local user with theidentifying information of the offline user received in offlineconversion data entry from the message, wherein the matching is basedon: assigning a confidence score to a match between the local user andthe offline user, and determining whether the confidence score meets apredetermined threshold; identifying one or more sponsored content itemsof the third party system that were presented within a range of aprevious time period to the identified local user during one or moreimpression opportunities at the online system; and determining anattribution amount of the offline conversion for each of the one or moresponsored content items that is inversely proportional to the timebetween a timestamp of the impression opportunity of the sponsoredcontent item and a timestamp of an occurrence of the offline conversion.35. The non-transitory computer-readable storage medium of claim 34,further comprising: computing an updated bid value for each of the oneor more sponsored content items for the identified local user, whereinthe updated bid value is increased or decreased based on correspondingattribution amounts for that sponsored content item, and wherein theupdated bid value is computed by the online system when submitting thesponsored content item for impression opportunities for the identifiedlocal user.
 36. The non-transitory computer-readable storage medium ofclaim 34, further comprising: transmitting instructions to a clientdevice associated with the third party system to cause the client deviceto display a user interface presenting additional information regardingthe offline conversion to the third party system, wherein the additionalinformation comprises a conversion rate of the one or more sponsoredcontent items computed using stored offline conversion data, and whereinthe additional information was not previously accessible to the thirdparty system.
 37. The non-transitory computer-readable storage medium ofclaim 36, wherein the transmitting instructions to present additionalinformation regarding the offline conversion further comprises:transmitting, to the third party system, a conversion rate of thesponsored content based on a number of local users with stored offlineconversion data attributed to the sponsored content item and a totalnumber of local users presented with the sponsored content item.
 38. Thenon-transitory computer-readable storage medium of claim 37, wherein theconversion rate is based on at least one of: type of action performed byoffline users as indicated by the stored offline conversion data; orvisual placement of the attributed sponsored content item when thesponsored content item was presented to the local users in the onlinesystem.
 39. The non-transitory computer-readable storage medium of claim34, wherein the action is not directly trackable by the online systemvia a website of the third party system.
 40. The non-transitorycomputer-readable storage medium of claim 34, wherein the actioncomprises at least one of: a transaction at a physical location, atransaction as part of a delayed payment service, a transaction as partof a service approval process, or a transaction completed at anintermediary.